mirror of
https://github.com/leejet/stable-diffusion.cpp.git
synced 2026-09-25 07:27:53 -05:00
feat: add verbose logging and log-level selection (#1941)
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+20
-20
@@ -421,11 +421,11 @@ bool ModelManager::load_tensors_to_params_backend(const std::vector<TensorState*
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}
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}
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for (const auto& entry : prepared) {
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LOG_DEBUG("model manager prepared params backend buffers (%6.2f MB, %zu tensors, %zu blocks, %s) on %s",
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entry.second.bytes / (1024.f * 1024.f),
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entry.second.tensors, entry.second.blocks,
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ggml_backend_buft_is_host(entry.first) ? "RAM" : "VRAM",
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ggml_backend_buft_name(entry.first));
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LOG_VERBOSE("model manager prepared params backend buffers (%6.2f MB, %zu tensors, %zu blocks, %s) on %s",
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entry.second.bytes / (1024.f * 1024.f),
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entry.second.tensors, entry.second.blocks,
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ggml_backend_buft_is_host(entry.first) ? "RAM" : "VRAM",
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ggml_backend_buft_name(entry.first));
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}
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return true;
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@@ -547,12 +547,12 @@ bool ModelManager::stage_tensors_to_compute_backend(const std::vector<TensorStat
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if (!stage_chunk(chunk)) {
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return false;
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}
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LOG_DEBUG("model manager staged compute params (%6.2f MB, %zu tensors, %zu blocks) to %s, taking %.2fs",
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staged_bytes / (1024.f * 1024.f),
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target_states.size(),
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staged_blocks,
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ggml_backend_name(compute_backend),
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(ggml_time_ms() - t0) / 1000.f);
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LOG_VERBOSE("model manager staged compute params (%6.2f MB, %zu tensors, %zu blocks) to %s, taking %.2fs",
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staged_bytes / (1024.f * 1024.f),
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target_states.size(),
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staged_blocks,
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ggml_backend_name(compute_backend),
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(ggml_time_ms() - t0) / 1000.f);
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}
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return true;
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@@ -809,10 +809,10 @@ bool ModelManager::alloc_params_buffers(const std::vector<TensorState*>& states,
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initialized->data = nullptr;
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initialized->extra = nullptr;
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}
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LOG_DEBUG("model manager releasing params backend buffer (%6.2f MB, %zu tensors, %s)",
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ggml_backend_buffer_get_size(buffer) / (1024.f * 1024.f),
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initialized_tensors.size(),
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ggml_backend_buffer_is_host(buffer) ? "RAM" : "VRAM");
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LOG_VERBOSE("model manager releasing params backend buffer (%6.2f MB, %zu tensors, %s)",
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ggml_backend_buffer_get_size(buffer) / (1024.f * 1024.f),
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initialized_tensors.size(),
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ggml_backend_buffer_is_host(buffer) ? "RAM" : "VRAM");
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ggml_backend_buffer_free(buffer);
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return false;
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}
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@@ -1107,11 +1107,11 @@ void ModelManager::release_params_storage_blocks(bool force,
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}
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}
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for (const auto& entry : released) {
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LOG_DEBUG("model manager released params backend buffers (%6.2f MB, %zu tensors, %zu blocks, %s) from %s",
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entry.second.bytes / (1024.f * 1024.f),
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entry.second.tensors, entry.second.blocks,
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ggml_backend_buft_is_host(entry.first) ? "RAM" : "VRAM",
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ggml_backend_buft_name(entry.first));
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LOG_VERBOSE("model manager released params backend buffers (%6.2f MB, %zu tensors, %zu blocks, %s) from %s",
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entry.second.bytes / (1024.f * 1024.f),
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entry.second.tensors, entry.second.blocks,
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ggml_backend_buft_is_host(entry.first) ? "RAM" : "VRAM",
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ggml_backend_buft_name(entry.first));
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}
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}
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